1. Field of the Invention
The invention relates to image processing and statistical analysis of digitized images of carcasses of meat animals to determine grade and yield parameters of the carcass.
2. Description of the Related Art
Meat animal grading, in both live animals and carcasses, has typically been performed by human graders, introducing substantial subjectivity to the grading process. There are two main aspects to meat grading, quality grade and yield grade. Quality grade of young animals is determined by the amount of intramuscular fat (marbling) in the meat. Yield grade describes the proportion of lean tissue in the carcass.
In the carcass, grading is usually conducted by observation and measurement of a cross-section of the longissimus dorsi (described in beef as the "rib eye muscle" and in hogs as the "loin eye muscle"). Quality grade or marbling is typically determined by comparing the appearance of the rib eye with reference photographs of rib eyes of carcasses of known quality grades. The grader can assess the quality grade by comparing the amount of marbling in the rib eye being examined with the amount of marbling seen in the reference photographs.
The proportion of lean tissue in the carcass (yield grade) is typically estimated from the area of the rib eye and the thickness of subcutaneous fat at various sites around the rib eye. Yield grade calculations may also involve body cavity fat measurements and hot carcass weight. As will be discussed in greater detail herein, various definitions of a "yield grade" are possible as they may depend on particular carcass processing standards. A particularly useful measure of yield grade is the "saleable yield" of the carcass which reflects the proportion of the live weight of the animal made up by the sum of the weight of the saleable cuts plus the weight of the trim. Typically, saleable yield is determined upon butchering of the carcass into standard cuts of meat.
A number of automated meat processing systems have made use of the different light reflecting properties of muscle tissue versus fatty tissue. U.S. Pat. No. 5,324,228 (Vogeley, issued Jun. 28, 1994) describes a method and apparatus for illuminating a fish fillet with a stripe of light as it is viewed by a pair of video cameras. Light brightness signals from the cameras are converted by a computer to electric digital signals representing illumination brightness. The computer compares the digital signals to a pre-selected threshold of grey scale levels to locate peripheral fat areas. The computer then controls the operation of a cutter mechanism to remove the areas of fat. Similar systems for distinguishing light coloured edible loin meat from dark coloured inedible waste meat in tuna slices are described in U.S. Pat. No. 3,800,363 (Lapeyre, issued Apr. 2, 1974) and U.S. Pat. No. 4,738,004 (Lapeyre, issued Apr. 19, 1988).
U.S. Pat. No. 3,154,625 (Kail, issued Oct. 27, 1964) describes a method for determining the marbling of a carcass rib eye by measuring the average reflectivity of a rib eye relative to the reflectivity of a fat coloured sample plate, using a photometer.
U.S. Pat. No. 4,413,279 (Gorl, issued Nov. 1, 1983) describes an improved method for calculating a brightness threshold for distinguishing fat from lean tissue to overcome problems in identifying tissues of intermediate brightness, such as blood-smeared fat, for use in meat grading systems wherein the relative brightness of various tissues are recorded with a video camera.
U.S. Pat. No. 5,352,153 (Burch et al., issued Oct. 4, 1994) describes an apparatus for illuminating and acquiring video images of fish sections during processing.
U.S. Pat. No. 4,226,540 (Barten et al., issued Oct. 7, 1980) describes a method for determining features of meat quality in which the ratio of fat to lean tissue is determined by scanning a meat product with a moving beam of light and discriminating fat from lean tissue based on the differing brightness values of fat and tissue.
A number of video imaging grading systems have been described in which a series of images are taken of live animals. U.S. Pat. No. 5,483,441 (Scofield et al., issued Jan. 9, 1996) describes a video image acquisition and analysis system wherein a series of video images are acquired and evaluated as a live animal moves through successive fields of view. U.S. Pat. No. 4,745,472 (Hayes et al., issued May 17, 1988) describes a video image acquisition and analysis system wherein markers are placed on various anatomical reference points on the body of a live animal. The animal is then positioned in a chute having top and side walls comprising measurement grids. Video tape recordings are made of the animal in the chute, and the video information is analysed with a computer to determine the distances between the markers manually attached to the animal's body.
Other systems have combined video imaging information with other information acquired by, for instance, inserting a probe into the carcass, to provide grading information. U.S. Pat. No. 4,939,574 (Petersen et al., issued Jul. 3, 1990) describes a light-screening chamber in which the silhouette of an animal carcass is recorded with an electronic camera and the contour of the carcass determined with a data processing system. Carcass contour information is used in conjunction with a previous carcass colour assessment and meat and fat thickness information determined by insertion of a probe into the carcass, to determine a carcass classification.
U.S. Pat. No. 4,439,037 (Northeved et al., issued Mar. 27, 1984) describes an optical probe for insertion into a carcass to assess the meat-to-lard ratio of the carcass.
Ultrasound images of live animals have been analysed for the purpose of estimating the marbling or subcutaneous fat thickness of the animal. U.S. Pat. No. 4,785,817 (Stouffer, issued Nov. 22, 1988) describes an apparatus and method for using ultrasound for determining the thickness of fat on various parts of a carcass from which grading determinations can be made. Similarly, U.S. Pat. No. 5,339,815 (Liu et al., issued Aug. 23, 1994), addressing ultrasonic imaging of beef cattle, teaches associating the autocorrelation property of ultrasound speckle noise with beef marbling score.
International Application WO 93/21597 (Benn et al., International Filing Date--Apr. 13, 1993) teaches one method for tracing the outline of a digital image of a rib eye muscle of a carcass in which links are defined between pairs of concavities in the rib eye outline in order to excise image sections external to the rib eye.
International Application WO 92/00523 (Newman, International Filing Date--Jun. 24, 1991) describes a method of grading carcasses after slaughter involving the steps of checking for the presence of a carcass in the field of view of a camera, checking that the carcass is properly oriented with respect to the camera, acquiring images of the carcass from a plurality of viewpoints, determining a plurality of dimensions of the carcass from the images and comparing the dimensions with stored values to determine a grade for the carcass. However, there is no description of how the dimensions of the carcass might be determined or how they could be related to the carcass grade.
International Application WO 91/14180 (Benn, International Filing Date Mar. 14, 1991) describes a method for evaluating carcasses by object image processing involving the steps of recording an image of a background, recording a second image of a carcass positioned in front of the background, analysing the first and second images to differentiate the carcass from the background by subtracting the first or second image from the other for each colour component to provide a series of component difference images which are recombined to provide an absolute difference image. The application states that anatomical points can be identified on the carcass by comparing the area of the carcass profile with a series of reference profiles, and matching the anatomical points of the images having the most similar area. It is stated that quantitative dimensional measurements can be taken from anatomical points to predict composition, but there is no description of how to make the quantitative measurements, which ones might be useful, or how to make a prediction based on the measurements.
In concluding, the systems described above do not permit continuous grade or yield calculations of carcasses to be made during the slaughtering procedure. Techniques are needed to reliably take accurate and reproducible measurements of carcass dimensions without manual identification of anatomical features of the carcass and to develop yield predictions based on these carcass measurements. This requires the identification of specific definite and reproducible carcass measurements that are closely correlated to the grade or yield parameter of interest. Refined rib eye tracing techniques are also required to obtain accurate rib eye measurements which may also be used in grade and yield determinations.